Analysis of modern approaches to load balancing of server clusters in educational information systems and corresponding algorithm
https://doi.org/10.32517/0234-0453-2025-40-2-79-87
Abstract
Learning Management Systems (LMS) play a critical role in the educational process, providing students with a variety of educational content, and teachers with tools for monitoring students’ knowledge and assessing progress. However, as the number of students increases, the load on data transmission channels also increases, potentially leading to a decline in the quality of education. To solve this problem, a comprehensive approach to load balancing within server clusters of educational platforms is required.
The article reviews the main existing load balancing algorithms, provides a comparative analysis, and assesses their applicability to educational platforms. Particular attention is paid to Content Delivery Networks (CDN) and their critical role in the process. Modern trends in integrating load balancers with cloud technologies are analyzed, emphasizing the importance of intelligent cache management and container orchestration as key methods for increasing the performance and fault tolerance of LMS platforms. A server cluster architecture based on 1C:Enterprise 8 is proposed, along with practical schemes for building scalable infrastructures for online learning.
About the Authors
R. V. SuschenyaRussian Federation
Roman V. Suschenya, Postgraduate Student at the Department of Information Control in Technical Systems, Faculty of Information Technologies; Software Developer,
Moscow
V. E. Petrov
Russian Federation
Valery E. Petrov, Candidate of Sciences (Engineering), Docent, Associate Professor at the Department of Information Control in Technical Systems, Faculty of Information Technologies,
Moscow.
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Review
For citations:
Suschenya R.V., Petrov V.E. Analysis of modern approaches to load balancing of server clusters in educational information systems and corresponding algorithm. Informatics and education. 2025;40(2):79-87. (In Russ.) https://doi.org/10.32517/0234-0453-2025-40-2-79-87